Code for this DE analysis can be found at
maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/code/DEAnalysis.Rmd.
I performed DE analysis using the edgeR package and its pipeline (https://bioconductor.org/packages/release/bioc/html/edgeR.html)
3dpa-intact
6dpa-intact
6dpa-intact
9dpa-intact
12dpa-intact
15dpa-intact
21dpa-intact
28dpa-intact
3dpa-1dpa
6dpa-3dpa
9dpa-6dpa
12dpa-9dpa
15dpa-12dpa
21dpa-15dpa
28dpa-21dpa
intact-28dpa
Can be found at
maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/data/tables/DEAnalysis/DEGenes/logFC2-cutoff/de/
I noticed that the amount of genes obtained with these cutoffs where
low in some of the comparisons, so I decided to plot the amount of DE
genes along the different comparisons. Code can be found at
maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/code/PlotDE-ct_logFC2-1e-5.Rmd.
Given there are comparisons with few DEs I will loose the logFC cuttoff so I can use a bigger list to run GO term.